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Observational constraints on dark matter–dark energy scattering cross section

2017· article· en· W2750900636 on OpenAlexaboutno aff

Bibliographic record

VenueThe European Physical Journal C · 2017
Typearticle
Languageen
FieldPhysics and Astronomy
TopicDark Matter and Cosmic Phenomena
Canadian institutionsnot available
FundersScience and Engineering Research BoardDepartment of Science and Technology, Ministry of Science and Technology, India
KeywordsDark energyCosmic microwave backgroundPlanckScatteringCosmologyWeak gravitational lensingDark matterObservational cosmologyBaryon acoustic oscillationsGravitational lens

Abstract

fetched live from OpenAlex

In this letter, we report precise and robust observational constraints on the dark matter–dark energy scattering cross section, using the latest data from cosmic microwave background (CMB) Planck temperature and polarization, baryon acoustic oscillations (BAO) measurements and weak gravitational lensing data from Canada–France–Hawaii Telescope Lensing Survey (CFHTLenS). The scattering scenario consists of a pure momentum exchange between the dark components, and we find $$\sigma _d < 10^{-29} \, \mathrm{cm^2} \, (m_\mathrm{dm} \, c^2/\mathrm{Gev})$$ at 95% CL from the joint analysis (CMB + BAO + CFHTLenS), where $$m_\mathrm{dm}$$ is a typical dark matter particle mass. We notice that the scattering among the dark components may influence the growth of large scale structure in the Universe, leaving the background cosmology unaltered.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.007
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.016

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.007
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.002
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.027
GPT teacher head0.269
Teacher spread0.242 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations54
Published2017
Admission routes1
Has abstractyes

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